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Role of HSP90 in the Regulation of de Novo Purine Biosynthesis

Overview of attention for article published in Biochemistry, March 2018
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Article details
Title
Role of HSP90 in the Regulation of de Novo Purine Biosynthesis
Published in
Biochemistry, March 2018
DOI 10.1021/acs.biochem.8b00140
Pubmed ID
Authors
Abstract

Despite purines making up one of the largest classes of metabolites in a cell, little is known about the regulatory mechanisms that facilitate efficient purine production. Under conditions resulting in high purine demand, enzymes within the de novo purine biosynthetic pathway cluster into multienzyme assemblies called purinosomes. Purinosome formation has been linked to molecular chaperones HSP70 and HSP90; however, the involvement of these molecular chaperones in purinosome formation remains largely unknown. Here, we present a new-found biochemical mechanism for the regulation of de novo purine biosynthetic enzymes mediated through HSP90. HSP90-client protein interaction assays were employed to identify two enzymes within the de novo purine biosynthetic pathway, PPAT and FGAMS, as client proteins of HSP90. Inhibition of HSP90 by STA9090 abrogated these interactions and resulted in a decrease in the level of available soluble client protein while having no significant effect on their interactions with HSP70. These findings provide a mechanism to explain the dependence of purinosome assembly on HSP90 activity. The combined efforts of molecular chaperones in the maturation of PPAT and FGAMS result in purinosome formation and are likely essential for enhancing the rate of purine production to meet intracellular purine demand.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 6 18%
Student > Doctoral Student 3 9%
Student > Bachelor 3 9%
Professor 3 9%
Unspecified 1 3%
Other 3 9%
Unknown 14 42%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 24%
Agricultural and Biological Sciences 4 12%
Chemistry 3 9%
Unspecified 1 3%
Immunology and Microbiology 1 3%
Other 2 6%
Unknown 14 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 March 2018.
All research outputs
#21,866,582
of 24,395,432 outputs
Outputs from Biochemistry
#21,462
of 22,293 outputs
Outputs of similar age
#297,311
of 336,084 outputs
Outputs of similar age from Biochemistry
#150
of 177 outputs
Altmetric has tracked 24,395,432 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,293 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 336,084 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 177 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.